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Found 1,204 Skills
Run 397B parameter Mixture-of-Experts LLMs on a MacBook using pure C/Metal with SSD streaming
Official Reference Guide for the PPIO Platform, covering LLM API (OpenAI-compatible), Agent Sandbox, GPU (Instances and Serverless), integration, authentication, pricing, rate limiting, and troubleshooting. Suitable for common questions such as 'How to integrate PPIO in specific application scenarios?' and PPIO request failures.
Build with Surf pay-per-use APIs at surf.cascade.fyi. Twitter data, Reddit data, web search/crawl, and LLM inference - no signup, no API keys, just pay per call. Use when working with Surf endpoints, fetching Twitter/X data, Reddit data, web crawling/search, pay-per-request LLM inference, setting up x402-proxy or @x402/fetch with Surf, or any mention of surf.cascade.fyi. Triggers on surf, surf.cascade.fyi, surf API, twitter data, reddit data, web crawl, surf inference, x402 endpoints, MCP surf tools.
Fetch and compile arXiv papers on LLMs, autonomous agents, and AI infrastructure into scored, grouped research digests. Stores digests at ~/.aibtc/arxiv-research/digests/. No API key required.
This skill should be used when the user asks to "audit a website for AI visibility", "scan a domain", "check AI readiness", "evaluate content quality", "run a Morphiq Scan", "check if a site is optimized for LLMs", or mentions scanning a website for LLM citation readiness. Performs a full AI visibility audit across 5 categories (agentic readiness, content quality, chunking & retrieval, query fanout, policy files) and scores the domain on a 100-point rubric.
Adds an "AI Summary Request" footer component with clickable AI platform icons (ChatGPT, Claude, Gemini, Grok, Perplexity) that pre-populate prompts for users to get AI summaries of the website. Optionally creates an llms.txt file for enhanced AI discoverability. Use when users want to add AI platform integration buttons or make their website AI-friendly.
Core patterns for AI coding agents based on analysis of Claude Code, Codex, Cline, Aider, OpenCode. Triggers when: Building an AI coding agent or assistant, implementing tool-calling loops, managing context windows for LLMs, setting up agent memory or skill systems, or designing multi-provider LLM abstraction. Capabilities: Core agent loop with while(true) and tool execution, context management with pruning and compression and repo maps, tool safety with sandboxing and approval flows and doom loop detection, multi-provider abstraction with unified API for different LLMs, memory systems with project rules and auto-memory and skill loading, session persistence with SQLite vs JSONL patterns.
Set up and maintain a persistent, LLM-managed knowledge base for a digital health project — turning clinical observations, papers, interviews, and planning docs into a compounding, interlinked wiki.
Build and maintain a personal knowledge base using Karpathy's llm-wiki methodology across Claude Code, Codex, and OpenClaw agents.
Connect to local LLM endpoints (Ollama, llama.cpp, vLLM) with automatic provider fallback. Use when: (1) you need to run LLM inference locally for privacy/cost, (2) you want to use models not available via cloud APIs, (3) you need offline capability, (4) you want automatic fallback to cloud providers when local fails.
Design WhatsApp LLM chatbots for East African markets: conversation flows, social presence principles, trust-building, local language registers, and human escalation protocols. Invoke when a client wants to automate WhatsApp customer service, sales enquiries, or support using AI.
Text analytics using LLM APIs — sentiment analysis, customer feedback classification, document entity extraction, multi-language support (English/Luganda/Swahili), feedback aggregation, and NLP feature implementation for PHP/Android/iOS. Sources...